Human-mediated hybridization threatens many native species, but the effects of introgressive hybridization on life-history expression are rarely quantified, especially in vertebrates. We quantified the effects of non-native rainbow trout admixture on important life-history traits including growth and partial migration behavior in three populations of westslope cutthroat trout over five years. Rainbow trout admixture was associated with increased summer growth rates in all populations and decreased spring growth rates in two populations with cooler spring temperatures. These results indicate that non-native admixture may increase growth under warmer conditions, but cutthroat trout have higher growth rates during cooler periods. Non-native admixture consistently increased expression of migratory behavior, suggesting that there is a genomic basis for life-history differences between these species. Our results show that effects of interspecific hybridization on fitness traits can be the product of genotype-by-environment interactions even when there are minor differences in environmental optima between hybridizing species. These results also indicate that while environmentally mediated traits like growth may play a role in population-level consequences of admixture, strong genetic influences on migratory life-history differences between these species likely explains the continued spread of non-native hybridization at the landscape-level, despite selection against hybrids at the population-level.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.13163","usgsCitation":"Strait, J., Eby, L., Kovach, R., Muhlfeld, C.C., Boyer, M., Amish, S.J., Smith, S., Lowe, W., and Luikart, G., 2021, Hybridization alters growth and migratory life-history expression of native trout: Evolutionary Applications, v. 14, p. 821-833, https://doi.org/10.1111/eva.13163.","productDescription":"13 p.","startPage":"821","endPage":"833","ipdsId":"IP-120443","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":454307,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.13163","text":"Publisher Index Page"},{"id":387126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.213623046875,\n 47.04766864046083\n ],\n [\n -111.64306640625,\n 47.04766864046083\n ],\n [\n -111.64306640625,\n 49.009050809382046\n ],\n [\n -115.213623046875,\n 49.009050809382046\n ],\n [\n -115.213623046875,\n 47.04766864046083\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Strait, Jeffrey 0000-0002-0901-3911","orcid":"https://orcid.org/0000-0002-0901-3911","contributorId":260879,"corporation":false,"usgs":false,"family":"Strait","given":"Jeffrey","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eby, Lisa A","contributorId":251751,"corporation":false,"usgs":false,"family":"Eby","given":"Lisa A","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kovach, Ryan P.","contributorId":126724,"corporation":false,"usgs":false,"family":"Kovach","given":"Ryan P.","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":819041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyer, Matthew","contributorId":124595,"corporation":false,"usgs":false,"family":"Boyer","given":"Matthew","affiliations":[{"id":5133,"text":"Montana Fish Wildlife and Parks, Kalispell, Montana 59901","active":true,"usgs":false}],"preferred":false,"id":819043,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Amish, Stephen J.","contributorId":104799,"corporation":false,"usgs":false,"family":"Amish","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":819044,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Seth","contributorId":189234,"corporation":false,"usgs":false,"family":"Smith","given":"Seth","email":"","affiliations":[],"preferred":false,"id":819045,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lowe, Winsor H.","contributorId":64532,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor H.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":819046,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Luikart, Gordon","contributorId":124531,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":5091,"text":"Flathead Lake Biological Station, Fish and Wildlife Genomics Group, Division of Biological Sciences, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":819047,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70211530,"text":"70211530 - 2021 - Foreword","interactions":[],"lastModifiedDate":"2021-04-19T16:35:11.260297","indexId":"70211530","displayToPublicDate":"2020-11-03T11:30:33","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Foreword","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Spatial dynamics and ecology of large ungulate populations in tropical forests of India","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","usgsCitation":"Royle, J.A., 2021, Foreword, chap. of Spatial dynamics and ecology of large ungulate populations in tropical forests of India, p. vii-ix.","productDescription":"3 p.","startPage":"vii","endPage":"ix","ipdsId":"IP-118087","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":385201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":376861,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/book/10.1007%2F978-981-15-6934-0#toc"}],"country":"India","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[77.83745,35.49401],[78.91227,34.32194],[78.81109,33.5062],[79.20889,32.99439],[79.17613,32.48378],[78.45845,32.61816],[78.73889,31.51591],[79.72137,30.88271],[81.11126,30.18348],[80.47672,29.72987],[80.08842,28.79447],[81.0572,28.4161],[81.99999,27.92548],[83.30425,27.36451],[84.67502,27.2349],[85.25178,26.7262],[86.02439,26.63098],[87.22747,26.3979],[88.06024,26.41462],[88.1748,26.81041],[88.04313,27.44582],[88.12044,27.87654],[88.73033,28.08686],[88.81425,27.29932],[88.83564,27.09897],[89.74453,26.7194],[90.37327,26.87572],[91.21751,26.80865],[92.03348,26.83831],[92.10371,27.45261],[91.69666,27.77174],[92.50312,27.89688],[93.41335,28.64063],[94.56599,29.27744],[95.4048,29.03172],[96.11768,29.4528],[96.58659,28.83098],[96.24883,28.41103],[97.32711,28.26158],[97.40256,27.88254],[97.05199,27.69906],[97.134,27.08377],[96.41937,27.26459],[95.12477,26.57357],[95.15515,26.00131],[94.60325,25.1625],[94.55266,24.67524],[94.10674,23.85074],[93.32519,24.07856],[93.28633,23.04366],[93.06029,22.70311],[93.16613,22.27846],[92.67272,22.04124],[92.14603,23.6275],[91.86993,23.62435],[91.70648,22.98526],[91.15896,23.50353],[91.46773,24.07264],[91.91509,24.13041],[92.3762,24.97669],[91.7996,25.14743],[90.87221,25.1326],[89.92069,25.26975],[89.83248,25.96508],[89.35509,26.01441],[88.56305,26.44653],[88.20979,25.76807],[88.93155,25.23869],[88.30637,24.86608],[88.08442,24.50166],[88.69994,24.23371],[88.52977,23.63114],[88.87631,22.87915],[89.03196,22.05571],[88.88877,21.69059],[88.2085,21.70317],[86.9757,21.49556],[87.03317,20.74331],[86.49935,20.15164],[85.06027,19.47858],[83.94101,18.30201],[83.18922,17.67122],[82.19279,17.01664],[82.19124,16.55666],[81.69272,16.31022],[80.792,15.95197],[80.3249,15.89918],[80.02507,15.13641],[80.23327,13.83577],[80.28629,13.00626],[79.86255,12.05622],[79.858,10.35728],[79.34051,10.30885],[78.88535,9.54614],[79.18972,9.21654],[78.27794,8.93305],[77.94117,8.25296],[77.5399,7.96553],[76.59298,8.89928],[76.13006,10.29963],[75.74647,11.30825],[75.3961,11.78125],[74.86482,12.74194],[74.61672,13.99258],[74.44386,14.61722],[73.5342,15.99065],[73.11991,17.92857],[72.82091,19.20823],[72.82448,20.4195],[72.63053,21.35601],[71.17527,20.75744],[70.47046,20.87733],[69.16413,22.0893],[69.64493,22.45077],[69.3496,22.84318],[68.17665,23.69197],[68.8426,24.35913],[71.04324,24.35652],[70.8447,25.2151],[70.28287,25.72223],[70.16893,26.49187],[69.51439,26.94097],[70.6165,27.9892],[71.77767,27.91318],[72.82375,28.96159],[73.45064,29.97641],[74.42138,30.97981],[74.40593,31.69264],[75.25864,32.27111],[74.45156,32.7649],[74.10429,33.44147],[73.74995,34.3177],[74.2402,34.74889],[75.75706,34.50492],[76.87172,34.65354],[77.83745,35.49401]]]},\"properties\":{\"name\":\"India\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":794529,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70228230,"text":"70228230 - 2021 - Sibship reconstruction with SNPs illuminates the scope of a cryptic invasion of Asian Swamp Eels (Monopterus albus) in Georgia, USA","interactions":[],"lastModifiedDate":"2022-02-14T12:25:38.150683","indexId":"70228230","displayToPublicDate":"2020-11-03T11:28:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Sibship reconstruction with SNPs illuminates the scope of a cryptic invasion of Asian Swamp Eels (Monopterus albus) in Georgia, USA","title":"Sibship reconstruction with SNPs illuminates the scope of a cryptic invasion of Asian Swamp Eels (Monopterus albus) in Georgia, USA","docAbstract":"Cryptic invasive species are particularly problematic to study, manage, and control because of the difficulty detecting these species within their invaded habitats. Such is the case of the Asian Swamp Eel (Monopterus albus; ASE) where it is established in vegetated marshes along the Chattahoochee River, Georgia. Adult eels have been nearly impossible to detect or quantify with traditional sampling, although leaf-litter trapping of juvenile ASEs has been somewhat successful. In this study, we leveraged a collection of juveniles from the 2015 cohort and used single-nucleotide polymorphisms to reconstruct sibship among these juveniles in COLONY. Sibship reconstruction allowed us to learn about adult breeding behaviors and provided the first quantified estimates of breeder abundance. Pedigree reconstruction revealed that adults of both sexes were polygamous and likely traveled up to 0.5 km among marsh habitats during a single breeding season. Estimates of the number of breeding adults contributing to offspring (Ns) and the effective number of breeders (Nb) indicated an approximate minimum bound of 100 breeding adults in the marshes in 2015. Our study updated the invasion status of a cryptic population formerly riddled with uncertainty, highlighting that low captures of adult eels in the study area have been the result of low detectability, not low abundance. Given that low detectability would likely hinder removal efforts, our results suggest that future efforts could focus on suppression of ASE abundance when they are most vulnerable to capture and containing the spatial extent of the invasion.
","language":"English","publisher":"Springer Link","doi":"10.1007/s10530-020-02384-5","usgsCitation":"Taylor, A., Bangs, M.R., and Long, J.M., 2021, Sibship reconstruction with SNPs illuminates the scope of a cryptic invasion of Asian Swamp Eels (Monopterus albus) in Georgia, USA: Biological Invasions, v. 23, p. 569-580, https://doi.org/10.1007/s10530-020-02384-5.","productDescription":"12 p.","startPage":"569","endPage":"580","ipdsId":"IP-109886","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Chattahoochee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.39371109008789,\n 33.9874951489\n ],\n [\n -84.36555862426758,\n 33.9874951489\n ],\n [\n -84.36555862426758,\n 34.0079888707242\n ],\n [\n -84.39371109008789,\n 34.0079888707242\n ],\n [\n -84.39371109008789,\n 33.9874951489\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2020-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, A. T.","contributorId":274894,"corporation":false,"usgs":false,"family":"Taylor","given":"A. T.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":833486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bangs, M. R.","contributorId":274895,"corporation":false,"usgs":false,"family":"Bangs","given":"M.","email":"","middleInitial":"R.","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":833487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833488,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216442,"text":"70216442 - 2021 - A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity","interactions":[],"lastModifiedDate":"2021-03-05T21:58:59.699233","indexId":"70216442","displayToPublicDate":"2020-11-03T06:58:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity","docAbstract":"Community occupancy models estimate species‐specific parameters while sharing information across species by treating parameters as sampled from a common distribution. When communities consist of discrete groups, shrinkage of estimates towards the community mean can mask differences among groups. Infinite mixture models using a Dirichlet process (DP) distribution, in which the number of latent groups is estimated from the data, have been proposed as a solution. In addition to community structure, these models estimate species similarity, which allows testing hypotheses about whether traits drive species response to environmental conditions. We develop a community occupancy model (COM) using a DP distribution to model species‐level parameters. Because clustering algorithms are sensitive to dimensionality and distinctiveness of clusters, we conducted a simulation study to explore performance of the DP‐COM with different dimensions (i.e., different numbers of model parameters with species‐level DP random effects) and under varying cluster differences. Because the DP‐COM is computationally expensive, we compared its estimates to a COM with a normal random species effect. We further applied the DP‐COM model to a bird dataset from Uganda. Estimates of the number of clusters and species cluster identity improved with increasing difference among clusters and increasing dimensions of the DP; but the number of clusters was always overestimated. Estimates of number of sites occupied and species and community level covariate coefficients on occupancy probability were generally unbiased with (near‐) nominal 95% Bayesian Credible Interval coverage. Accuracy of estimates from the normal and the DP‐COM were similar. The DP‐COM clustered 166 bird species into 27 clusters regarding their affiliation with open or woodland habitat and distance to oil wells. Estimates of covariate coefficients were similar between a normal and the DP‐COM. Except sunbirds, species within a family were not more similar in their response to these covariates than the overall community. Given that estimates were consistent between the normal and the DP‐COM, and considering the computational burden for the DP models, we recommend using the DP‐COM only when the analysis focuses on community structure and species similarity, as these quantities can only be obtained under the DP‐COM.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2249","usgsCitation":"Sollmann, R., Eaton, M.J., Link, W., Mulundo, P., Ayebare, S., Prinsloo, S., Plumptre, A.J., and Johnson, D., 2021, A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity: Ecological Applications, v. 31, no. 2, e2249, https://doi.org/10.1002/eap.2249.","productDescription":"e2249","ipdsId":"IP-090810","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":454310,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eap.2249","text":"External Repository"},{"id":380583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Sollmann, Rahel 0000-0002-1607-2039","orcid":"https://orcid.org/0000-0002-1607-2039","contributorId":244998,"corporation":false,"usgs":false,"family":"Sollmann","given":"Rahel","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":805121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":805123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Link, William 0000-0002-9913-0256","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":221718,"corporation":false,"usgs":true,"family":"Link","given":"William","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":805122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mulundo, Paul","contributorId":245000,"corporation":false,"usgs":false,"family":"Mulundo","given":"Paul","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ayebare, Samuel","contributorId":245001,"corporation":false,"usgs":false,"family":"Ayebare","given":"Samuel","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prinsloo, Sarah","contributorId":245002,"corporation":false,"usgs":false,"family":"Prinsloo","given":"Sarah","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Plumptre, Andrew J.","contributorId":213154,"corporation":false,"usgs":false,"family":"Plumptre","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":805127,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, D.S.","contributorId":245003,"corporation":false,"usgs":false,"family":"Johnson","given":"D.S.","affiliations":[{"id":17856,"text":"National Marine Fisheries Service, NOAA","active":true,"usgs":false}],"preferred":false,"id":805128,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70236889,"text":"70236889 - 2021 - Damping values derived from surface-source, downhole-receiver measurements at 22 sites in the San Francisco Bay Area of central California and the San Fernando Valley of southern California","interactions":[],"lastModifiedDate":"2022-09-21T11:58:20.742945","indexId":"70236889","displayToPublicDate":"2020-11-03T06:55:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Damping values derived from surface-source, downhole-receiver measurements at 22 sites in the San Francisco Bay Area of central California and the San Fernando Valley of southern California","docAbstract":"A method discussed in Gibbs, Boore, et al. (1994) was applied to surface‐source, downhole‐receiver recordings at 22 boreholes, in the San Francisco Bay area in central California and the San Fernando Valley of southern California, to determine the average damping ratio of shear waves over depth intervals ranging from about 10 m to as much as 245 m (at one site), with most maximum depths being between 35 and 90 m. The average damping values range from somewhat less than 1% to almost 8%, with little dependence on grain size for sites in sediments. Surprisingly, the average damping values for sites with average velocities greater than about
Atlantic salmon populations in Maine remain critically low despite extensive hatchery supplementation and habitat improvement efforts. In 2000, the Gulf of Maine Distinct Population Segment was listed as Endangered under the ESA with joint listing authority shared by the National Oceanic and Atmospheric Administration (NOAA) and the United States Fish and Wildlife Service (USFWS). Because, regulators, and tribal, federal and state managers operate with independent authorities, recovery decisions depend upon effective communication and coordination among groups. Using a mixed-methods approach, we surveyed (n = 41) and interviewed (n = 28) members of the Atlantic Salmon Recovery Framework (ASRF), the joint governance structure responsible for Atlantic salmon management in Maine. We used survey results to examine the communication between members of ASRF through communication network analysis. While there is a relatively high network density for individual communication (56 %), connections are decentralized, a characteristic that can be incompatible with some organizational structures. Challenges reported by members fit into three general categories; i. slow and ineffective decision-making, ii. confusion surrounding leadership and accountability, and iii. low adaptive capacity. Despite these challenges, participants reported a commitment to maintaining a collaborative governance structure and a long history of inter-organizational relationships. This introspective effort has led to a reorganization effort to optimize communication pathways.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsci.2020.10.001","usgsCitation":"Flye, M.E., Sponarski, C.C., Zydlewski, J.D., and McGreavy, B., 2021, Understanding collaborative governance from a communication network perspective: A case study of the Atlantic Salmon recovery framework: Environmental Science and Policy, v. 115, p. 79-90, https://doi.org/10.1016/j.envsci.2020.10.001.","productDescription":"12 p.","startPage":"79","endPage":"90","ipdsId":"IP-115322","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":454314,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsci.2020.10.001","text":"Publisher Index Page"},{"id":395781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Gulf of Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.57617187499999,\n 42.69858589169842\n ],\n [\n -68.961181640625,\n 42.69858589169842\n ],\n [\n -67.181396484375,\n 43.36512572875844\n ],\n [\n -66.302490234375,\n 44.213709909702054\n ],\n [\n -66.961669921875,\n 44.96479793033101\n ],\n [\n -69.093017578125,\n 44.42593442145313\n ],\n [\n -70.77392578125,\n 43.42898792344155\n ],\n [\n -70.72998046875,\n 43.100982876188546\n ],\n [\n -70.57617187499999,\n 42.69858589169842\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"115","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Flye, Melissa. E.","contributorId":275664,"corporation":false,"usgs":false,"family":"Flye","given":"Melissa.","email":"","middleInitial":"E.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":834202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sponarski, Carly. C","contributorId":275665,"corporation":false,"usgs":false,"family":"Sponarski","given":"Carly.","email":"","middleInitial":"C","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":834203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":834201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGreavy, Bridie","contributorId":275231,"corporation":false,"usgs":false,"family":"McGreavy","given":"Bridie","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":834204,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217747,"text":"70217747 - 2021 - Transport and speciation of uranium in groundwater-surface water systems impacted by legacy milling operations","interactions":[],"lastModifiedDate":"2021-02-01T14:29:48.935866","indexId":"70217747","displayToPublicDate":"2020-11-02T06:35:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Transport and speciation of uranium in groundwater-surface water systems impacted by legacy milling operations","docAbstract":"Growing worldwide concern over uranium contamination of groundwater resources has placed an emphasis on understanding uranium transport dynamics and potential toxicity in groundwater-surface water systems. In this study, we utilized novel in-situ sampling methods to establish the location and magnitude of contaminated groundwater entry into a receiving surface water environment, and to investigate the speciation and potential bioavailability of uranium in groundwater and surface water. Streambed temperature mapping successfully identified the location of groundwater entry to the Little Wind River, downgradient from the former Riverton uranium mill site, Wyoming, USA. Diffusive equilibrium in thin-film (DET) samplers further constrained the groundwater plume and established sediment pore water solute concentrations and patterns. In this system, evidence is presented for attenuation of uranium-rich groundwater in the shallow sediments where surface water and groundwater interaction occurs. Surface water grab and DET sampling successfully detected an increase in river uranium concentrations where the groundwater plume enters the Little Wind River; however, concentrations remained below environmental guideline levels. Uranium speciation was investigated using diffusive gradients in thin-film (DGT) samplers and geochemical speciation modelling. Together, these investigations indicate uranium may have limited bioavailability to organisms in the Little Wind River and, possibly, in other similar sites in the western U.S.A. This could be due to ion competition effects or the presence of non- or partially labile uranium complexes. Development of methods to establish the location of contaminated (uranium) groundwater entry to surface water environments, and the potential effects on ecosystems, is crucial to develop both site-specific and general conceptual models of uranium behavior and potential toxicity in affected ground and surface water environments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.143314","usgsCitation":"Byrne, P.A., Fuller, C.C., Naftz, D.L., Runkel, R.L., Lehto, N.J., and Dam, W., 2021, Transport and speciation of uranium in groundwater-surface water systems impacted by legacy milling operations: Science of the Total Environment, v. 761, 143314, 11 p., https://doi.org/10.1016/j.scitotenv.2020.143314.","productDescription":"143314, 11 p.","ipdsId":"IP-121496","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":454315,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1776309","text":"Publisher Index Page"},{"id":382831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","city":"Riverton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.39832305908203,\n 43.00816202648563\n ],\n [\n -108.33995819091797,\n 43.00816202648563\n ],\n [\n -108.33995819091797,\n 43.03175685183966\n ],\n [\n -108.39832305908203,\n 43.03175685183966\n ],\n [\n -108.39832305908203,\n 43.00816202648563\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"761","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Byrne, Patrick A.","contributorId":247578,"corporation":false,"usgs":false,"family":"Byrne","given":"Patrick","email":"","middleInitial":"A.","affiliations":[{"id":49583,"text":"Liverpool John Moores University","active":true,"usgs":false}],"preferred":false,"id":809453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":809454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Naftz, David L. 0000-0003-1130-6892 dlnaftz@usgs.gov","orcid":"https://orcid.org/0000-0003-1130-6892","contributorId":1041,"corporation":false,"usgs":true,"family":"Naftz","given":"David","email":"dlnaftz@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809456,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lehto, Niklas J","contributorId":248588,"corporation":false,"usgs":false,"family":"Lehto","given":"Niklas","email":"","middleInitial":"J","affiliations":[{"id":49952,"text":"Lincoln University","active":true,"usgs":false}],"preferred":false,"id":809457,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dam, William L","contributorId":248589,"corporation":false,"usgs":false,"family":"Dam","given":"William L","affiliations":[{"id":49955,"text":"Conserve-Prosper LLC","active":true,"usgs":false}],"preferred":false,"id":809458,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216402,"text":"70216402 - 2021 - Thinking like a consumer: Linking aquatic basal metabolism and consumer dynamics","interactions":[],"lastModifiedDate":"2021-02-03T23:53:16.73024","indexId":"70216402","displayToPublicDate":"2020-10-31T08:26:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Thinking like a consumer: Linking aquatic basal metabolism and consumer dynamics","docAbstract":"The increasing availability of high‐frequency freshwater ecosystem metabolism data provides an opportunity to identify links between metabolic regimes, as gross primary production and ecosystem respiration patterns, and consumer energetics with the potential to improve our current understanding of consumer dynamics (e.g., population dynamics, community structure, trophic interactions). We describe a conceptual framework linking metabolic regimes of flowing waters with consumer community dynamics. We use this framework to identify three emerging research needs: (1) quantifying the linkage of metabolism and consumer production data via food web theory and carbon use efficiencies, (2) evaluating the roles of metabolic dynamics and other environmental regimes (e.g., hydrology, light) in consumer dynamics, and (3) determining the degree to which metabolic regimes influence the evolution of consumer traits and phenology. Addressing these needs will improve the understanding of consumer biomass and production patterns as metabolic regimes can be viewed as an emergent property of food webs.
Global biodiversity is in unprecedented decline and on-the-ground solutions are imperative for conservation. Although there is a large volume of evidence related to climate change effects on wildlife, research on climate adaptation strategies is lagging. To assess the current state of knowledge in climate adaptation, we conducted a comprehensive literature review and evaluated 1,346 peer-reviewed publications for management recommendations designed to address the consequences of climate change on wildlife populations. From 509 publications, we identified 2,306 recommendations and employed both qualitative and quantitative methods for data analysis. Although we found an increase in the volume and diversity of recommendations since 2007, a focus on protected areas (26%, 596 of 2,306 recommendations) and the non-reserve matrix (12%, 276 of 2,306 recommendations) remained prominent in the climate adaptation literature. Common concepts include protected areas, invasive species, ecosystem services, adaptive management, stepping stones, assisted migration, and conservation easements. In contrast, only 1% of recommendations focused on reproduction (n = 26), survival (n = 14), disease (n = 26), or human-wildlife conflict (n = 24). Few recommendations reflected the potential for local-scale management interventions. We demonstrate limited advancement in preparing natural resource managers in climate adaptation at local, management-relevant scales. Additional research is needed to identify and evaluate climate adaptation strategies aimed at reducing the vulnerability of wildlife to contemporary climate change. © 2020 The Wildlife Society.
Near-surface soil conditions can significantly alter the amplitude and frequency content of incoming ground motions – often with profound consequences for the built environment – and are thus important inputs to any ground-motion prediction. Previous soil-velocity models (SVM) have predicted shear-wave velocity profiles based on the time-averaged shear-wave velocity in the upper 30 m (VS30). This article presents a generic soil-velocity model that accounts both for near-surface conditions (VS30) and deeper geologic structure, as represented to the depth at which the profile reaches a velocity of 1.0 km/s (Z1.0). To demonstrate the advantages of our new SVM, we apply it to the Cascadia Region of North America, where numerous geologic basins and glaciated landscapes give rise to a wide range of VS30 and Z1.0 combinations. This soil velocity model yields good estimates of site response across all site conditions, and significantly improves upon a model calibrated using only VS30 data. In conjunction with existing models that describe the deep velocity structure of the region (e.g., (Stephenson et al., 2017) [27]; the proposed model is particularly suited for use in regional-scale predictions of site response, liquefaction, landslides, infrastructure damage, and loss. The proposed methodology is broadly applicable to the development of SVMs elsewhere, and with improved understanding of near-surface and deep velocity structures, can facilitate more accurate ground-motion predictions globally.
International efforts to restore degraded ecosystems will continue to expand over the coming decades, yet the factors contributing to the effectiveness of long‐term restoration across large areas remain largely unexplored. At large scales, outcomes are more complex and synergistic than the additive impacts of individual restoration projects. Here, we propose a cumulative‐effects conceptual framework to inform restoration design and implementation and to comprehensively measure ecological outcomes. To evaluate and illustrate this approach, we reviewed long‐term restoration in several large coastal and riverine areas across the US: the greater Florida Everglades; Gulf of Mexico coast; lower Columbia River and estuary; Puget Sound; San Francisco Bay and Sacramento–San Joaquin Delta; Missouri River; and northeastern coastal states. Evidence supported eight modes of cumulative effects of interacting restoration projects, which improved outcomes for species and ecosystems at landscape and regional scales. We conclude that cumulative effects, usually measured for ecosystem degradation, are also measurable for ecosystem restoration. The consideration of evidence‐based cumulative effects will help managers of large‐scale restoration capitalize on positive feedback and reduce countervailing effects.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.2274","usgsCitation":"Diefenderfer, H.L., Steyer, G., Harwell, M.C., LoSchiavo, A.J., Neckles, H.A., Burdick, D.M., Johnson, G.E., Buenau, K.E., Trujillo, E., Callaway, J.C., Thom, R.M., Ganju, N., and Twilley, R.R., 2021, Applying cumulative effects to strategically advance large‐scale ecosystem restoration: Frontiers in Ecology and the Environment, v. 19, no. 2, p. 108-117, https://doi.org/10.1002/fee.2274.","productDescription":"10 p.","startPage":"108","endPage":"117","ipdsId":"IP-107430","costCenters":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"links":[{"id":454325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.2274","text":"Publisher Index Page"},{"id":385579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico, San Francisco Bay/Sacramento Delta, Puget Sound, Gulf of Maine, Virginia Coastal Bays, Lower Columbia River and Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.66796875,\n 25.562265014427492\n ],\n [\n -82.44140625,\n 25.562265014427492\n ],\n [\n -82.44140625,\n 30.372875188118016\n ],\n [\n -99.66796875,\n 30.372875188118016\n ],\n [\n -99.66796875,\n 25.562265014427492\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.1484375,\n 45.398449976304086\n ],\n [\n -70.400390625,\n 44.33956524809713\n ],\n [\n -74.35546875,\n 40.78054143186033\n ],\n [\n -77.16796875,\n 38.95940879245423\n ],\n [\n -76.728515625,\n 36.80928470205937\n ],\n [\n -74.1796875,\n 36.59788913307022\n ],\n [\n 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hneckles@usgs.gov","orcid":"https://orcid.org/0000-0002-5662-2314","contributorId":3821,"corporation":false,"usgs":true,"family":"Neckles","given":"Hilary","email":"hneckles@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":815458,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burdick, David M.","contributorId":208047,"corporation":false,"usgs":false,"family":"Burdick","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37687,"text":"Jackson Estuarine Laboratory, Univesity of New Hampshire, Durham, NH","active":true,"usgs":false}],"preferred":false,"id":815459,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Gary E.","contributorId":257982,"corporation":false,"usgs":false,"family":"Johnson","given":"Gary","email":"","middleInitial":"E.","affiliations":[{"id":52195,"text":"Pacific Northwest National 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0000-0002-7364-286X","orcid":"https://orcid.org/0000-0002-7364-286X","contributorId":205456,"corporation":false,"usgs":false,"family":"Callaway","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37110,"text":"Dept. of Environmental Science, University of San Francisco, 2130 Fulton St., San Francisco, CA 94117","active":true,"usgs":false}],"preferred":false,"id":815463,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thom, Ronald M. 0000-0002-8639-6709","orcid":"https://orcid.org/0000-0002-8639-6709","contributorId":257985,"corporation":false,"usgs":false,"family":"Thom","given":"Ronald","email":"","middleInitial":"M.","affiliations":[{"id":52195,"text":"Pacific Northwest National Lab","active":true,"usgs":false}],"preferred":false,"id":815464,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":815465,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Twilley, Robert R.","contributorId":34585,"corporation":false,"usgs":false,"family":"Twilley","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":815466,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70216772,"text":"70216772 - 2021 - Evaluation of seismic hazard models with fragile geologic features","interactions":[],"lastModifiedDate":"2021-01-19T16:04:47.842953","indexId":"70216772","displayToPublicDate":"2020-10-28T09:20:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of seismic hazard models with fragile geologic features","docAbstract":"We provide an overview of a 2019 workshop on the use of fragile geologic features (FGFs) to evaluate seismic hazard models. FGFs have been scarcely utilized in the evaluation of seismic hazard models, despite nearly 30 yr having passed since the first recognition of their potential value. Recently, several studies have begun to focus on the implementation of FGFs in seismic hazard modeling. The workshop was held to capture a “snapshot” of the state‐of‐the‐art in FGF work and to define key research areas that would increase confidence in FGF‐based evaluation of seismic hazard models. It was held at the annual meeting of the Southern California Earthquake Center on 8 September 2019, and the conveners were Mark Stirling (University of Otago, New Zealand) and Michael Oskin (University of California, Davis). The workshop attracted 44 participants from a wide range of disciplines. The main topics of discussion were FGF fragility age estimation (age at which an FGF achieved its current fragile geometry), fragility estimation, FGF‐based evaluation of seismic hazard models, and ethical considerations relating to documentation and preservation of FGFs. There are now many scientists working on, or motivated to work on, FGFs, and more types of FGFs are being worked on than just the precariously balanced rock (PBR) variety. One of the ideas presented at the workshop is that fragility ages for FGFs should be treated stochastically rather than assuming that all share a common age. In a similar vein, new studies propose more comprehensive methods of fragility assessment beyond peak ground acceleration and peak ground velocity‐based approaches. Two recent studies that apply PBRs to evaluate probabilistic seismic hazard models use significantly different methods of evaluation. Key research needs identified from the workshop will guide future, focused efforts that will ultimately facilitate the uptake of FGFs in seismic hazard analysis.
The global climate has been changing over the last century due to greenhouse gas emissions and will continue to change over this century, accelerating without effective global efforts to reduce emissions. Ticks and tick-borne diseases (TTBDs) are inherently climate-sensitive due to the sensitivity of tick lifecycles to climate. Key direct climate and weather sensitivities include survival of individual ticks, and the duration of development and host-seeking activity of ticks. These sensitivities mean that in some regions a warming climate may increase tick survival, shorten life-cycles and lengthen the duration of tick activity seasons. Indirect effects of climate change on host communities may, with changes in tick abundance, facilitate enhanced transmission of tick-borne pathogens. High temperatures, and extreme weather events (heat, cold, and flooding) are anticipated with climate change, and these may reduce tick survival and pathogen transmission in some locations. Studies of the possible effects of climate change on TTBDs to date generally project poleward range expansion of geographical ranges (with possible contraction of ranges away from the increasingly hot tropics), upslope elevational range spread in mountainous regions, and increased abundance of ticks in many current endemic regions. However, relatively few studies, using long-term (multi-decade) observations, provide evidence of recent range changes of tick populations that could be attributed to recent climate change. Further integrated ‘One Health’ observational and modeling studies are needed to detect changes in TTBD occurrence, attribute them to climate change, and to develop predictive models of public- and animal-health needs to plan for TTBD emergence.
","language":"English","publisher":"Entomological Society of America","doi":"10.1093/jme/tjaa220","usgsCitation":"Ogden, N.H., Beard, C.B., Ginsberg, H., and Tsao, J.I., 2021, Possible effects of climate change on ixodid ticks and the pathogens they transmit: Predictions and observations: Journal of Medical Entomology, v. 58, no. 4, p. 1536-1545, https://doi.org/10.1093/jme/tjaa220.","productDescription":"10 p.","startPage":"1536","endPage":"1545","ipdsId":"IP-121581","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":454330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jme/tjaa220","text":"Publisher Index Page"},{"id":379905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Ogden, Nicholas H.","contributorId":147667,"corporation":false,"usgs":false,"family":"Ogden","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":803337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beard, Charles B.","contributorId":148018,"corporation":false,"usgs":false,"family":"Beard","given":"Charles","email":"","middleInitial":"B.","affiliations":[{"id":16974,"text":"US Centers for Disease Control and Prevention (CDC)","active":true,"usgs":false}],"preferred":false,"id":803338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":803339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tsao, Jean I.","contributorId":140905,"corporation":false,"usgs":false,"family":"Tsao","given":"Jean","email":"","middleInitial":"I.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":803340,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216439,"text":"70216439 - 2021 - Estimating the contribution of tributary sand inputs to controlled flood deposits for sandbar restoration using elemental tracers, Colorado River, Grand Canyon National Park, Arizona","interactions":[],"lastModifiedDate":"2021-05-14T11:50:15.092644","indexId":"70216439","displayToPublicDate":"2020-10-28T07:37:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the contribution of tributary sand inputs to controlled flood deposits for sandbar restoration using elemental tracers, Colorado River, Grand Canyon National Park, Arizona","docAbstract":"Completion of Glen Canyon Dam in 1963 resulted in complete elimination of sediment delivery from the upstream Colorado River basin to Grand Canyon and nearly complete control of spring snowmelt floods responsible for creating channel and bar morphology. Management of the river ecosystem in Grand Canyon National Park now relies on dam-release floods to redistribute tributary-derived sediment accumulated on the channel bed to higher-elevation sandbars. Here, we used multivariate mixing analysis of sediment elemental compositions to evaluate the extent to which flood deposits derive from tributary-supplied sand compared to reworked, relict predam sediment. The concentrations of seven major and trace elements (Fe, Ca, K, Ti, Rb, Sr, and Zr) were measured in very fine−, fine-, and medium-grained sand from flood deposits using X-ray fluorescence and interpreted using a Bayesian mixing model to characterize the proportion of sand originating from the Paria River, the only major tributary within the study reach. Flood deposits from the 2013 and 2014 controlled floods contained 69% ± 16% and 84% ± 20% Paria River−derived material, respectively, with substantial variation among sites. Based on a sand mass balance, we calculated that under decreasing storage conditions since 1963, ∼77%−83% of the annual Paria River sand flux needs to be retained within the mass of active sand stored in Marble Canyon each year to reach the observed concentration of Paria River sand at sample locations. This finding suggests that the use of controlled floods may continue to be effective for sandbar maintenance, provided sand inputs from the Paria River do not decline.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35642.1","usgsCitation":"Chapman, K.A., Best, R.J., Smith, M.E., Mueller, E.R., Grams, P.E., and Parnell, R., 2021, Estimating the contribution of tributary sand inputs to controlled flood deposits for sandbar restoration using elemental tracers, Colorado River, Grand Canyon National Park, Arizona: Geological Society of America Bulletin, v. 133, no. 5-6, p. 1141-1156, https://doi.org/10.1130/B35642.1.","productDescription":"16 p.","startPage":"1141","endPage":"1156","ipdsId":"IP-116064","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":436648,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C0IN56","text":"USGS data release","linkHelpText":"Tributary sand input data, Colorado River, Grand Canyon National Park, Arizona"},{"id":380590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.027099609375,\n 35.71083783530009\n ],\n [\n -111.258544921875,\n 35.71083783530009\n ],\n [\n -111.258544921875,\n 36.958671131530316\n ],\n [\n -114.027099609375,\n 36.958671131530316\n ],\n [\n -114.027099609375,\n 35.71083783530009\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"133","issue":"5-6","noUsgsAuthors":false,"publicationDate":"2020-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Chapman, Katherine A. kchapman@usgs.gov","contributorId":5368,"corporation":false,"usgs":true,"family":"Chapman","given":"Katherine","email":"kchapman@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":805134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Best, Rebecca J.","contributorId":198804,"corporation":false,"usgs":false,"family":"Best","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":805135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, M. Elliot","contributorId":255572,"corporation":false,"usgs":false,"family":"Smith","given":"M.","email":"","middleInitial":"Elliot","affiliations":[],"preferred":false,"id":805136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mueller, Erich R. 0000-0001-8202-154X emueller@usgs.gov","orcid":"https://orcid.org/0000-0001-8202-154X","contributorId":4930,"corporation":false,"usgs":true,"family":"Mueller","given":"Erich","email":"emueller@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":812614,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":812615,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parnell, Roderic A.","contributorId":41922,"corporation":false,"usgs":true,"family":"Parnell","given":"Roderic A.","affiliations":[],"preferred":false,"id":812616,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216003,"text":"70216003 - 2021 - Carrying capacity of spatially distributed metapopulations","interactions":[],"lastModifiedDate":"2021-01-19T16:35:18.526261","indexId":"70216003","displayToPublicDate":"2020-10-28T07:32:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Carrying capacity of spatially distributed metapopulations","docAbstract":"Carrying capacity is a key concept in ecology. A body of theory, based on the logistic equation, has extended predictions of carrying capacity to spatially distributed, dispersing populations. However, this theory has only recently been tested empirically. The experimental results disagree with some theoretical predictions of when they are extended to a population dispersing randomly in a two-patch system. However, they are consistent with a mechanistic model of consumption on an exploitable resource (consumer–resource model). We argue that carrying capacity, defined as the total equilibrium population, is not a fundamental property of ecological systems, at least in the context of spatial heterogeneity. Instead, it is an emergent property that depends on the population’s intrinsic growth and dispersal rates.
Holocene crustal faulting in the northern Olympic Peninsula of Washington State manifests in a zone of west‐northwest‐striking crustal faults herein named the North Olympic fault zone, which extends for
Spatial and temporal patterns in low streamflows were investigated for 183 streamgages located in the Chesapeake Bay Watershed for the period 1939–2013. Metrics that represent different aspects of the frequency and magnitude of low streamflows were examined for trends: (1) the annual time series of seven‐day average minimum streamflow, (2) the scaled average deficit at or below the 2% mean daily streamflow value relative to a base period between 1939 and 1970, and (3) the annual number of days below the 2% threshold. Trends in these statistics showed spatial cohesion, with increasing low streamflow volume at streamgages located in the northern uplands of the Chesapeake Bay Watershed and decreasing low streamflow volume at streamgages in the southern part of the watershed. For a small subset of streamgages (12%), conflicting trend patterns were observed between the seven‐day average minimum streamflow and the below‐threshold time series and these appear to be related to upstream diversions or the influence of reservoir‐influenced streamflows in their contributing watersheds. Using multivariate classification techniques, mean annual precipitation and fraction of precipitation falling as snow appear to be broad controls of increasing and decreasing low‐flow trends. Further investigation of seasonal precipitation patterns shows summer rainfall patterns, driven by the Atlantic Multidecadal Oscillation, as the main driver of low streamflows in the Chesapeake Bay Watershed.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12892","usgsCitation":"Fleming, B.J., Archfield, S.A., Hirsch, R.M., Kiang, J.E., and Wolock, D.M., 2021, Spatial and temporal patterns of low streamflow and precipitation changes in the Chesapeake Bay Watershed: Journal of the American Water Resources Association, v. 57, no. 1, p. 96-108, https://doi.org/10.1111/1752-1688.12892.","productDescription":"13 p.","startPage":"96","endPage":"108","ipdsId":"IP-108281","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":454337,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12892","text":"Publisher Index Page"},{"id":436650,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J8Y8OE","text":"USGS data release","linkHelpText":"Low-streamflow and precipitation trends for 183 U.S. Geological Survey 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]\n}","volume":"57","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":809460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":809461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":809462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":809463,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228427,"text":"70228427 - 2021 - Habitat modelling locates nesting areas of the endangered Black-capped Petrel Pterodroma hasitata on Hispaniola and identifies habitat loss","interactions":[],"lastModifiedDate":"2022-02-10T15:43:03.162133","indexId":"70228427","displayToPublicDate":"2020-10-26T09:37:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1048,"text":"Bird Conservation International","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Habitat modelling locates nesting areas of the endangered Black-capped Petrel Pterodroma hasitata on Hispaniola and identifies habitat loss","title":"Habitat modelling locates nesting areas of the endangered Black-capped Petrel Pterodroma hasitata on Hispaniola and identifies habitat loss","docAbstract":"The Black-capped Petrel or Diablotin Pterodroma hasitata has a fragmented and declining population estimated at c.1,000 breeding pairs. On land, the species nests underground in steep ravines with dense understorey vegetation. The only confirmed breeding sites are located in the mountain ranges of Hispaniola in the Caribbean, where habitat loss and degradation are continuing threats. Other nesting populations may still remain undiscovered but, to locate them, laborious in situ nest searches must be conducted over expansive geographical areas. To focus nest-search efforts more efficiently, we analysed the environmental characteristics of Black-capped Petrel nesting habitat and modeled suitable habitat on Hispaniola using openly available environmental datasets. We used a univariate generalized linear model to compare the habitat characteristics of active Black-capped Petrel nests sites with those of potentially available sites (i.e. random pseudo-absences). Elevation, distance to coast, and the influence of tree cover and density emerged as important environmental variables. We then applied multivariate generalized linear models to these environmental variables that showed a significant relationship with petrel nesting activity. We used the top performing model of habitat suitability model to create maps of predicted suitability for Hispaniola. In addition to areas of known petrel activity, the model identified possible nesting areas for Black-capped Petrels in habitats not previously considered suitable. Based on model results, we estimated the total area of predicted suitable nesting habitat for Black-capped Petrels on Hispaniola and found that forest loss due to hurricanes, forest fires, and encroachment from agriculture had severely decreased availability of predicted suitable habitat between 2000 and 2018.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0959270920000490","usgsCitation":"Satge, Y.G., Rupp, E., Brown, A.J., and Jodice, P.G., 2021, Habitat modelling locates nesting areas of the endangered Black-capped Petrel Pterodroma hasitata on Hispaniola and identifies habitat loss: Bird Conservation International, v. 31, no. 4, p. 573-590, https://doi.org/10.1017/S0959270920000490.","productDescription":"18 p.","startPage":"573","endPage":"590","ipdsId":"IP-115786","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454339,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/s0959270920000490","text":"Publisher Index Page"},{"id":436651,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FWJPBD","text":"USGS data release","linkHelpText":"Nesting habitat suitability for the Black-capped Petrel Pterodroma hasitata on Hispaniola, Supplementary Material"},{"id":395771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Dominican Republic, Haiti","otherGeospatial":"Hispaniola","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.09326171875,\n 18.823116948090494\n ],\n [\n -69.2138671875,\n 19.621892180319374\n ],\n [\n -71.136474609375,\n 20.159098270646936\n ],\n [\n -72.916259765625,\n 20.24158281954221\n ],\n [\n -73.71826171874999,\n 19.766703551716976\n ],\n [\n -74.92675781249999,\n 18.396230138028827\n ],\n [\n -73.201904296875,\n 17.602139123350838\n ],\n [\n -71.47705078125,\n 17.45547257997284\n ],\n [\n -68.79638671875,\n 17.90556881196468\n ],\n [\n -68.21411132812499,\n 18.3336694457713\n ],\n [\n -68.09326171875,\n 18.823116948090494\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Satge, Y. G.","contributorId":275774,"corporation":false,"usgs":false,"family":"Satge","given":"Y.","email":"","middleInitial":"G.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":834273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rupp, E.","contributorId":265431,"corporation":false,"usgs":false,"family":"Rupp","given":"E.","email":"","affiliations":[],"preferred":false,"id":834274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, A. J.","contributorId":197185,"corporation":false,"usgs":false,"family":"Brown","given":"A.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":834275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834276,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215758,"text":"70215758 - 2021 - Surface elevation change evaluation in mangrove forests using a low‐cost, rapid‐scan terrestrial laser scanner","interactions":[],"lastModifiedDate":"2021-01-19T16:39:46.16129","indexId":"70215758","displayToPublicDate":"2020-10-26T08:13:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7183,"text":"Limnology and Oceanography Methods","active":true,"publicationSubtype":{"id":10}},"title":"Surface elevation change evaluation in mangrove forests using a low‐cost, rapid‐scan terrestrial laser scanner","docAbstract":"Mangrove forests have adapted to sea level rise (SLR) increases by maintaining their forest floor elevation via belowground root growth and surface sediment deposits. Researchers use surface elevation tables (SETs) to monitor surface elevation change (SEC) in mangrove forests, after which this information is used to assess SLR resiliency or to dictate active forest management for vulnerable systems. This method requires significant investments in terms of time and human resources and is limited in the number of points it can measure per plot. We use a low‐cost, portable terrestrial laser scanning (TLS) system to assess SEC for three mangrove forests on Pohnpei Island (Federated States of Micronesia). Cloth simulation filtering was used for ground detection, after which results were refined by filtering points using angular orientation. Digital elevation models then were generated via kriging interpolation for data collected in 2017 and 2019, after which the heights of corresponding points were compared across years. Extreme elevation changes, due to disturbances such as footprints or fallen logs, were removed using interquartile range analysis. The TLS‐obtained average SEC ranged between −6.92 and +6.01 mm, which exhibited an average consistency of 72% when compared to simultaneously collected SET data (root mean square error = 1.36 mm). We contend that this approach represents an improvement over the manual method, where very few points typically are used, that is, ≅ 36 points vs. ≅ 30,000 points in the case of TLS, and could contribute to improved monitoring and management of these rapidly changing forest environments.
The Cheboygan River, Michigan, is the only tributary to the upper Great Lakes where sea lamprey (Petromyzon marinus) are known to complete their entire life cycle. The Upper and Lower reaches are separated by the Cheboygan Lock and Dam located about 2 km from Lake Huron. In the Upper River, the Pigeon, Sturgeon, and Maple Rivers provide nursery habitat for larval sea lamprey. Burt and Mullett Lakes provide feeding grounds for juvenile sea lamprey. Low levels of immigration from Lake Huron occur when adult sea lamprey bypass the lock and dam. Lampricide treatment in the Pigeon, Sturgeon, and Maple Rivers began in 1966 and 15 treatments have been conducted to date at a combined cost of $435,000 USD per treatment. Treatments may become more difficult due to recent dam removals in the Pigeon (2016) and Maple Rivers (2018) that expanded habitat available to valued fishes and sea lamprey. At present, the landlocked population is less than 200 spawning adults, and those adults are generally smaller and may spawn earlier in the spring than adult sea lamprey from Lake Huron. Frequency of sea lamprey-induced wounding on steelhead (Oncorhynchus mykiss) and northern pike (Esox lucius) in Mullett Lake is less than 5%. Given increasing challenges of lampricide treatment, efforts to test other means of control such as sterile male release technique is on-going. The Cheboygan River represents a microcosm of the Great Lakes and is useful for learning about sea lamprey ecology and testing controls that supplement lampricides and barriers.
Many estuarine ecosystems and the fish communities that inhabit them have undergone substantial changes in the past several decades, largely due to multiple interacting stressors that are often of anthropogenic origin. Few are more impactful than droughts, which are predicted to increase in both frequency and severity with climate change. In this study, we examined over five decades of fish monitoring data from the San Francisco Estuary, California, USA, to evaluate the resistance and resilience of fish communities to disturbance from prolonged drought events. High resistance was defined by the lack of decline in species occurrence from a wet to a subsequent drought period, while high resilience was defined by the increase in species occurrence from a drought to a subsequent wet period. We found some unifying themes connecting the multiple drought events over the 50‐yr period. Pelagic fishes consistently declined during droughts (low resistance), but exhibit a considerable amount of resiliency and often rebound in the subsequent wet years. However, full recovery does not occur in all wet years following droughts, leading to permanently lower baseline numbers for some pelagic fishes over time. In contrast, littoral fishes seem to be more resistant to drought and may even increase in occurrence during dry years. Based on the consistent detrimental effects of drought on pelagic fishes within the San Francisco Estuary and the inability of these fish populations to recover in some years, we conclude that freshwater flow remains a crucial but not sufficient management tool for the conservation of estuarine biodiversity.
The western purple martin (Progne subis arboricola), an avian insectivore, is a species of conservation concern throughout the Pacific Northwest. Compared to the well-studied eastern subspecies (Progne subis subis), little is known of the life history and biology of the western subspecies. Availability of breeding habitat is believed to be a major limiting factor for western purple martins in forested habitat, but fundamental information on their current distribution and selection of nesting habitat is deficient. To fill this gap, we compared habitat characteristics at three spatial scales (snag-level, stand-level [48.6 ha], landscape-level [314 ha]) surrounding nest snags occupied by purple martins in western Oregon to unoccupied sites. We found habitat for nesting purple martins was defined by the presence of moderately decayed snags with nest cavities, located well away from closed-canopy forest in sufficiently large (>15 ha) open areas. Our modeling efforts suggested suitable habitat was rare within the study region because: 1) snags were scarce on private industrial forest lands and 2) large disturbed patches were uncommon on federal lands. We conclude that a disturbance regime characterized by infrequent but major stand-replacing events, such as fire or timber harvest, is likely the key to maintaining breeding habitat for purple martins in upland forests in western Oregon.
Lead poisoning, mainly through incidental ingestion of lead ammunition in carcasses, is a threat to scavenging and predatory bird species worldwide. In Australia, shooting for animal control is widespread, and a range of native scavenging species are susceptible to lead exposure. However, the prevalence of lead exposure in Australia's scavenging and predatory birds is largely unknown. We evaluated the degree to which the Tasmanian wedge‐tailed eagle (Aquila audax fleayi), an endangered Australian raptor and facultative scavenger, showed evidence of lead exposure. We detected lead in 100% of femur and liver tissues of 109 eagle carcasses opportunistically collected throughout Tasmania between 1996 and 2018. Concentrations were elevated in 10% of 106 liver (> 6 mg/kg dw) and 4% of 108 femur (> 10 mg/kg dw) samples. We also detected lead in 96% of blood samples taken from 24 live nestlings, with 8% at elevated concentrations (> 10 μg/dL). Of the liver samples with elevated lead, 73% had lead207/206 isotope ratios within the published range of lead‐based bullets available in Tasmania. These first comprehensive data on lead exposure of an Australian raptor are comparable to those for raptor studies elsewhere that identify lead‐based ammunition exposure as a conservation threat. Our findings highlight the importance of further research and efforts to address lead contamination throughout the Tasmanian ecosystem and in other Australian regions.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4914","usgsCitation":"Pay, J.M., Katzner, T., Hawkins, C.E., Koch, A.J., Wiersm, J.M., Brown, W.E., Mooney, N.J., and Cameron, E.Z., 2021, High frequency of lead exposure in the population of an endangered Australian top predator, the Tasmanian wedge-tailed eagle (Aquila audax fleayi): Environmental Toxicology and Chemistry, v. 40, no. 1, p. 219-230, https://doi.org/10.1002/etc.4914.","productDescription":"12 p.","startPage":"219","endPage":"230","ipdsId":"IP-114063","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":454349,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.4914","text":"Publisher Index Page"},{"id":380646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-10-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Pay, James M.","contributorId":245078,"corporation":false,"usgs":false,"family":"Pay","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":805305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":805217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawkins, Clare E.","contributorId":245079,"corporation":false,"usgs":false,"family":"Hawkins","given":"Clare","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":805306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koch, Amelia J.","contributorId":245080,"corporation":false,"usgs":false,"family":"Koch","given":"Amelia","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":805307,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiersm, Jason M.","contributorId":245081,"corporation":false,"usgs":false,"family":"Wiersm","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":805308,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, William E. 0000-0003-1595-9655","orcid":"https://orcid.org/0000-0003-1595-9655","contributorId":245082,"corporation":false,"usgs":false,"family":"Brown","given":"William","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":805309,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mooney, Nick J.","contributorId":245083,"corporation":false,"usgs":false,"family":"Mooney","given":"Nick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":805310,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cameron, Elissa Z.","contributorId":245084,"corporation":false,"usgs":false,"family":"Cameron","given":"Elissa","email":"","middleInitial":"Z.","affiliations":[],"preferred":false,"id":805311,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70219547,"text":"70219547 - 2021 - Relative abundance of coyotes (Canis latrans) influences gray fox (Urocyon cinereoargenteus) occupancy across the eastern United States","interactions":[],"lastModifiedDate":"2021-04-13T12:57:42.705789","indexId":"70219547","displayToPublicDate":"2020-10-22T07:56:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Relative abundance of coyotes (Canis latrans) influences gray fox (Urocyon cinereoargenteus) occupancy across the eastern United States","docAbstract":"Knowledge of the petrophysical and geomechanical properties of gas hydrate-bearing sediments is essential for predicting reservoir responses to gas production from gas hydrate reservoirs. In December 2018, Stratigraphic Test Well Hydrate-01 was drilled in the western part of the Prudhoe Bay Unit, Alaska North Slope, as part of the technical planning effort for a future long-term gas hydrate production test. Side-wall pressure coring was conducted to recover gas hydrate-bearing sediments from two reservoir sections named Unit B and Unit D. A total of 34 cores were successfully recovered during five runs of a wireline deployed pressure corer, and a total of 17 cores were preserved for advanced laboratory analysis. The samples were frozen inside the pressure core autoclave by liquid nitrogen while at high pressure before being removed and stored under liquid nitrogen at atmospheric pressure. High-resolution X-ray computed tomography showed the samples were high-quality, with undisturbed lithological layers. The Unit B and D sediments were categorized as sand or sandy silt with high hydrate saturation. Gas compositions suggest the hydrates formed with thermogenic and microbial mixed gases. Permeability tests and triaxial compression tests were conducted on the hydrate-bearing sediments. Low strengthening and high permeability at hydrate saturation Sh > 80% were observed. There was a small permeability reduction during the triaxial compression tests owing to porosity loss with increasing effective stress in the highly permeable sandy sediment after hydrate dissociation. The apparent minimal changes in porosity and permeability during the tests were due to the low-clay content and low compressibility of the quartz sand grains in the recovered cores. X-ray powder diffraction and thermal conductivity analysis also suggested a high quartz content for the analyzed samples.